code: def test_pettingzoo_env(self):
      register_env(
          "simple_spread",
          lambda _: PettingZooEnv(simple_spread_v3.env()),
      )
  
      config = (
          PPOConfig()
          .environment("simple_spread")
          .rollouts(num_rollout_workers=0, rollout_fragment_length=30)
          .debugging(log_level="DEBUG")
          .training(train_batch_size=200)
          .multi_agent(
              # Set of policy IDs (by default, will use Algorithm's
              # default policy class, the env's/agent's obs/act spaces and config={}).
              policies={"av"},
              # Mapping function that always returns "av" as policy ID to use
              # (for any agent).
              policy_mapping_fn=lambda agent_id, episode, worker, **kwargs: "av",
          )
      )
  
      algo = config.build()
      algo.train()
      algo.stop()
  
file_path: ray/rllib/tests/test_pettingzoo_env.py
imports: from numpy import float32
  from pettingzoo.butterfly import pistonball_v6
  from pettingzoo.mpe import simple_spread_v3
  from supersuit import color_reduction_v0, dtype_v0, normalize_obs_v0, observation_lambda_v0, resize_v1
  from supersuit.utils.convert_box import convert_box
  import unittest
  import ray
  from ray.rllib.algorithms.ppo import PPOConfig
  from ray.rllib.env import PettingZooEnv
  from ray.tune.registry import register_env
label_desc: Use image node_id 4 for calling the TestPettingZooEnv obj's underlying member method code with example usage: obj.test_pettingzoo_env() without return types